Datadog documentation is a static site generator project that publishes markdown content to the Datadog documentation site using Hugo.
The repository stores the source markdown files that power the Datadog documentation site. Hugo processes these markdown files to generate the static HTML documentation site. Contributors can edit documentation directly through GitHub's web interface via Edit buttons on published pages, or by forking the repository and submitting pull requests. The Documentation team reviews all contributions marked as ready for review.
The project welcomes external contributions and is suitable for anyone wanting to improve Datadog's documentation. Contributors should focus pull requests on addressing one or two specific problems rather than bundling many unrelated changes. The repository provides contribution guidelines and expects PR descriptions to be written by humans, explaining the problem being solved and the context for the change rather than listing individual modifications. The team emphasizes that while AI tools can assist in generating content, human review ensures quality standards are maintained before publication, and contributors should validate AI-generated content independently and plan timelines accordingly for review.
The project maintains active engagement with contributors through automated PR review assignment to the Documentation team. Pull requests receive human review and feedback, with the team requesting clarification on large changes and providing guidance on how to structure contributions. The team explicitly addresses content quality standards in their guidelines, distinguishing between acceptable contributions that solve specific problems and those that require additional validation before merging.
